Overview
Understand what Machine Learning is and how it differs from traditional programming., Explain supervised, unsupervised, and reinforcement learning in simple terms., Implement basic ML models in Python (Linear Regression, Classification)., Work with datasets using Pandas and visualize results with Matplotlib.
This course is designed for ICT professionals, developers, and beginners who want to enter the exciting world of machine learning but don’t know where to start., Have a background or interest in information and communication technology (ICT) and want to build coding skills in machine learning., Are software developers, data enthusiasts, or analysts looking to understand how AI and ML are applied in real-world systems., Are students, interns, or early-career professionals seeking practical skills that will make them more competitive in today’s data-driven job market., Want to learn step-by-step, hands-on using simple datasets, real examples, and free tools like Google Colab — without complex math or setup requirements., By the end of this course, learners will have a solid understanding of core ML concepts and the ability to build and test basic models in Python, opening doors to careers in data science, AI development, and automation.
This course is designed for absolute beginners — no prior experience in machine learning is required., Basic computer literacy: ability to use a web browser, download files, and open documents, Some familiarity with ICT concepts or programming logic (optional but helpful)., Access to the internet and a Google account (for running hands-on exercises in Google Colab — no installation needed)., A laptop or desktop computer with a modern web browser (Chrome, Edge, or Firefox)., While basic coding experience is an added advantage : all examples are explained step-by-step using clear Python code and datasets provided in the course resources.
Are you an ICT professional or developer looking to step into the world of Artificial Intelligence and Machine Learning? This course is designed to empower ICT developers with coding backgrounds, whether in Python, SQL, or general ICT systems to understand and implement basic machine learning concepts using Python. Our focus is on practical understanding and coding readiness, so you can start building real models without getting lost in complex theory.
Why This Course?
Machine learning is no longer a niche skill it’s a core competency for modern ICT professionals. Yet, many beginners struggle to bridge the gap between theory and practice. This course solves that problem by providing step-by-step, hands-on guidance using Google Colab, a free cloud-based platform that eliminates installation hassles and gives you access to powerful computing resources like GPUs.
What You’ll Learn
The course is structured into six concise modules that fit into just one hour of learning:
Introduction to Machine Learning
Understand what ML is, how it differs from traditional programming, and explore real-world applications. Learn the ML pipeline and where it fits in ICT systems.ML Concepts & Terminology
Get familiar with essential terms like datasets, features, labels, training vs testing, and algorithms. Learn the difference between supervised and unsupervised learning in simple language.Setting Up Your ML Environment
Learn how to set up Python and work in Google Colab. Install key libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib, all without complicated configurations.Hands-On: Your First ML Model
Build your first machine learning model using Linear Regression. Load a dataset, train the model, visualize predictions, and evaluate accuracy, all in Colab.Hands-On: Classification Example
Move from prediction to classification with Logistic Regression. Understand binary classification and learn how to interpret a confusion matrix.Next Steps & Career Roadmap
Discover how to advance your skills beyond this course. Learn about portfolio building, intermediate ML topics, and career paths in AI and data science.
Louisa Muparuri
Dr Louisa Muparuri is a seasoned ICT expert with a passion for Education. She has over 20 years of experience in general ICTs, training, software development, ICT strategy formulation and implementation, Artificial Intelligence and its applications in business, and many more. She holds a PhD in Mathematics, Honours in Data Science and in Computer Science, Master's in Operations Research and Statistics, Master's in Business Administration, and many professional certifications from renowned industry leaders such as Microsoft, Oracle, and Google.